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Luppar: Information Retrieval for Closed Text Document Collections

Fabiano Tavares da Silva, Jos´e Everardo Bessa Maia in Information Sciences

International Journal of Applied Information Systems
Year of Publication:2020
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Fabiano Tavares da Silva, Jos´e Everardo Bessa Maia
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  1. Fabiano Tavares Silva and Jose Everardo Bessa Maia. Luppar: Information Retrieval for Closed Text Document Collections. International Journal of Applied Information Systems 12(28):1-6, March 2020. URL, DOI BibTeX

    	author = "Fabiano Tavares da Silva and Jose Everardo Bessa Maia",
    	title = "Luppar: Information Retrieval for Closed Text Document Collections",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "March 2020",
    	volume = 12,
    	number = 28,
    	month = "March",
    	year = 2020,
    	issn = "2249-0868",
    	pages = "1-6",
    	url = "",
    	doi = "10.5120/ijais2020451846",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


This article presents Luppar, an Information Retrieval tool for closed collections of text documents which uses a local distributional semantic model associated to each corpus. The system performs automatic query expansion using a combination of distributional semantic model and local context analysis and supports relevancy feedback. The performance of the system was evaluated in databases of different domains and presented results equal to or higher than those published in the literature.


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Information Retrieval, Distributional Semantic Model, Local Context Analysis, Closed Document Collection